Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Más filtros

Banco de datos
Tipo del documento
País de afiliación
Intervalo de año de publicación
2.
Sensors (Basel) ; 16(8)2016 Aug 03.
Artículo en Inglés | MEDLINE | ID: mdl-27527167

RESUMEN

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98 . 30 % ( ± 1 . 26 % ) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.


Asunto(s)
Electromiografía/métodos , Higiene de las Manos , Dispositivos Electrónicos Vestibles , Algoritmos , Antebrazo/fisiología , Humanos , Reconocimiento de Normas Patrones Automatizadas
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA